Abstract
A method for impulse noise detection and removal in color images comprising a detection module and a vector median filter.
Highlights
The major sources of noise corrupted in most digital images are from the process of image acquisition, quantization, and transmission
Our objective is to design an efficient algorithm for detection and removal of the random-valued impulse noise in color images based on the fundamentals of Moran’s I (MI) statistics and Laplacian kernels
Please note that in the noise levels 10% and 15%, both robust switching vector median filter (RSVMF) and Moran’s I vector median filter (MIVMF) were run twice to obtain the best outcome measured by peak signal-to-noise ratio (PSNR)
Summary
The major sources of noise corrupted in most digital images are from the process of image acquisition, quantization, and transmission. The consequence of degraded images can create potential problems for further image processing and analysis. A clustering algorithm for segmenting an image usually measures the relationships in the pixel space by categorizing the pixels into different classes.[2] the existence of noise pixels will create different attributes for pixels that originally belonged to the same cluster. Our goal is to remove noise in color images and restore the image, which, as a result, will be as similar as possible or identical to the original image
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